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Congress: ECR25
Poster Number: C-11257
Type: Poster: EPOS Radiologist (scientific)
Authorblock: M. Swoboda, J. Deeg, D. Egle, V. Ladenhauf, M. Galijašević, S. Haushammer, B. Amort, M. Pamminger, L. Gruber; Innsbruck/AT
Disclosures:
Michael Swoboda: Nothing to disclose
Johannes Deeg: Nothing to disclose
Daniel Egle: Nothing to disclose
Valentin Ladenhauf: Nothing to disclose
Malik Galijašević: Nothing to disclose
Silke Haushammer: Nothing to disclose
Birgit Amort: Nothing to disclose
Mathias Pamminger: Nothing to disclose
Leonhard Gruber: Nothing to disclose
Keywords: Artificial Intelligence, Breast, Oncology, Elastography, Ultrasound, Diagnostic procedure, Cancer
Purpose

Breast cancer is the most frequently diagnosed cancer and the second leading cause of cancer-related deaths among women. Breast ultrasound is an effective tool for distinguishing between cystic and solid masses and for identifying suspicious features of solid masses that may warrant a biopsy. Nevertheless, many breast lesions may initially appear similar to fibroadenomas on ultrasound and can mimic benign morphological characteristics of fibroadenomas on ultrasound, making the differentiation between benign fibroadenomas and malignant tumors of the breast mimicking fibroadenomas (MTMF) challenging. The objective of this retrospective study is to evaluate the reliability of ultrasound in distinguishing between fibroadenomas and malignant breast tumors that mimic fibroadenomas (MTMF), as well as to identify imaging features suggestive of malignancy.

GALLERY